particle swarm optimization
[/ˈpɑːrtɪkəl swɔːrm ˌɒptɪmaɪˈzeɪʃən/]
noun
otimização por enxame de partículas
1. A computational technique inspired by the social behavior of bird flocking or fish schooling, used to find optimal solutions to problems by simulating the movement and interaction of particles in a search space.
Particle swarm optimization is commonly used to solve complex engineering and optimization problems.
A otimização por enxame de partículas é comumente usada para resolver problemas complexos de engenharia e otimização.
2. A metaheuristic algorithm where candidate solutions (particles) move through the problem space, influenced by their own best position and the best position found by the entire swarm.
The algorithm uses particle swarm optimization to find the best parameters for the neural network.
O algoritmo utiliza otimização por enxame de partículas para encontrar os melhores parâmetros da rede neural.
This is a technical term primarily used in computer science, artificial intelligence, and engineering fields. It is used identically in both Brazil and Portugal in academic and professional settings. The term is often abbreviated as 'PSO' in international technical literature. Given its specialized nature, it is rarely used outside of technical or academic contexts.
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